The English Benedictines, 1540-1688: From reformation to revolution

Lunn, David

Barnes&Noble

SCIENCEFOCUS 10

Webb, Michael

McGuire, Barry

Mason, Adrienne

Gue, David

Jeans, Stephen

Hutton, Glen

Searle, Sandy

Leong, Ed

Painter, Danika

Siler, Richard

Science & Math

McGraw-Hill/Ryerson

Light wear to the prce clipped dust jacket. Shipped from the UK in recyclable card packaging.

The English Benedictines, 1540-1688 : From Reformation to Revolution

Burns & Oates, Barnes & Noble

The Wetwang Saga: The Story of Fridaythorpe, Fimber and Wetwang, a History of England in Two and a Half Parishes

High Wolds Heritage Group

The BUGS Book (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity. It also features a large number of worked examples and a wide range of applications from various disciplines. The book introduces regression models, techniques for criticism and comparison, and a wide range of modelling issues before going into the vital area of hierarchical models, one of the most common applications of Bayesian methods. It deals with essentials of modelling without getting bogged down in complexity. The book emphasises model criticism, model comparison, sensitivity analysis to alternative priors, and thoughtful choice of prior distributions�all those aspects of the "art" of modelling that are easily overlooked in more theoretical expositions. More pragmatic than ideological, the authors systematically work through the large range of "tricks" that reveal the real power of the BUGS software, for example, dealing with missing data, censoring, grouped data, prediction, ranking, parameter constraints, and so on. Many of the examples are biostatistical, but they do not require domain knowledge and are generalisable to a wide range of other application areas. Full code and data for examples, exercises, and some solutions can be found on the book�s website.

The BUGS Book: A Practical Introduction to Bayesian Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Computers & Technology

Thomas, Andrew

Jackson, Chris

Spiegelhalter, David

Best, Nicky

Programming Languages

Chapman and Hall/CRC

Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity. It also features a large number of worked examples and a wide range of applications from various disciplines. The book introduces regression models, techniques for criticism and comparison, and a wide range of modelling issues before going into the vital area of hierarchical models, one of the most common applications of Bayesian methods. It deals with essentials of modelling without getting bogged down in complexity. The book emphasises model criticism, model comparison, sensitivity analysis to alternative priors, and thoughtful choice of prior distributions―all those aspects of the "art" of modelling that are easily overlooked in more theoretical expositions. More pragmatic than ideological, the authors systematically work through the large range of "tricks" that reveal the real power of the BUGS software, for example, dealing with missing data, censoring, grouped data, prediction, ranking, parameter constraints, and so on. Many of the examples are biostatistical, but they do not require domain knowledge and are generalisable to a wide range of other application areas. Full code and data for examples, exercises, and some solutions can be found on the book’s website.

Mathematics

Routledge

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